{"citation":{"ieee":"E. Yang, N. H. Barton, T. Arslan, and A. Erdogan, “A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks,” presented at the WCCI: IEEE World Congress on Computational Intelligence, 2008, pp. 2749–2756.","ama":"Yang E, Barton NH, Arslan T, Erdogan A. A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks. In: IEEE; 2008:2749-2756. doi:<a href=\"https://doi.org/10.1109/CEC.2008.4631167\">10.1109/CEC.2008.4631167</a>","chicago":"Yang, Erfu, Nicholas H Barton, Tughrul Arslan, and Ahmet Erdogan. “A Novel Shifting Balance Theory-Based Approach to Optimization of an Energy-Constrained Modulation Scheme for Wireless Sensor Networks,” 2749–56. IEEE, 2008. <a href=\"https://doi.org/10.1109/CEC.2008.4631167\">https://doi.org/10.1109/CEC.2008.4631167</a>.","mla":"Yang, Erfu, et al. <i>A Novel Shifting Balance Theory-Based Approach to Optimization of an Energy-Constrained Modulation Scheme for Wireless Sensor Networks</i>. IEEE, 2008, pp. 2749–56, doi:<a href=\"https://doi.org/10.1109/CEC.2008.4631167\">10.1109/CEC.2008.4631167</a>.","ista":"Yang E, Barton NH, Arslan T, Erdogan A. 2008. A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks. WCCI: IEEE World Congress on Computational Intelligence, 2749–2756.","apa":"Yang, E., Barton, N. H., Arslan, T., &#38; Erdogan, A. (2008). A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks (pp. 2749–2756). Presented at the WCCI: IEEE World Congress on Computational Intelligence, IEEE. <a href=\"https://doi.org/10.1109/CEC.2008.4631167\">https://doi.org/10.1109/CEC.2008.4631167</a>","short":"E. Yang, N.H. Barton, T. Arslan, A. Erdogan, in:, IEEE, 2008, pp. 2749–2756."},"publist_id":"1861","type":"conference","publisher":"IEEE","status":"public","month":"09","quality_controlled":0,"year":"2008","date_created":"2018-12-11T12:07:49Z","publication_status":"published","date_updated":"2021-01-12T07:55:34Z","page":"2749 - 2756","_id":"4244","author":[{"full_name":"Yang, Erfu","last_name":"Yang","first_name":"Erfu"},{"orcid":"0000-0002-8548-5240","full_name":"Nicholas Barton","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H"},{"full_name":"Arslan, Tughrul","last_name":"Arslan","first_name":"Tughrul"},{"last_name":"Erdogan","full_name":"Erdogan, Ahmet T","first_name":"Ahmet"}],"day":"23","conference":{"name":"WCCI: IEEE World Congress on Computational Intelligence"},"date_published":"2008-09-23T00:00:00Z","doi":"10.1109/CEC.2008.4631167","abstract":[{"lang":"eng","text":"This paper presents a new approach to optimization of an energy-constrained modulation scheme for wireless sensor networks by taking advantage of a novel bio-inspired optimization algorithm. The algorithm is inspired by Wrightpsilas shifting balance theory (SBT) of evolution in population genetics. The total energy consumption of an energy-constrained modulation scheme is minimized by using the new SBT-based optimization algorithm. The results obtained by this new algorithm are compared with other popular optimization algorithms. Numerical experiments are performed to demonstrate that the SBT-based algorithm could be used as an efficient optimizer for solving the optimization problems arising from currently emerging energy-efficient wireless sensor networks."}],"extern":1,"title":"A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks"}